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Record W4212949776 · doi:10.5296/ijhrs.v12i1.19462

Employee Engagement Outlooks in the Era of COVID-19: Implications for Human Resource Management

2022· article· en· W4212949776 on OpenAlex
Olawunmi Elizabeth Eniola

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueInternational Journal of Human Resource Studies · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCOVID-19 Pandemic Impacts
Canadian institutionsUniversity of Regina
FundersUniversity of Regina
KeywordsEmployee engagementWorkforceCoronavirus disease 2019 (COVID-19)Public relationsPandemicHuman resource managementWork engagementHuman resourcesEmployee resource groupsPower (physics)Work (physics)Community engagementBusinessPsychologyPolitical scienceEmployee researchManagementEconomicsMedicine

Abstract

fetched live from OpenAlex

The severe COVID-19 pandemic triggered an extraordinary global health crisis, resulting in an economic downturn and negative consequences for employees' work lives, especially employee engagement. An overview of how literature has been tackling the impact of COVID-19 on employee engagement is still missing. Hence, this article illustrates how literature has addressed the development and maintenance of employee engagement in various parts of the world due to the global health crisis. The report discusses individual and organizational roles in fostering employee engagement. The article provides general ideas for researchers interested in extending employee engagement studies under critical situations. It also highlights the consideration for human resource management in both individual and organizational contexts. As well, equips organizational leaders and human resource practitioners with productive and enabling power for informed decision-making about improving employee engagement of their workforce during the ongoing pandemic or other stressful events.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.627
Threshold uncertainty score0.554

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.154
GPT teacher head0.389
Teacher spread0.235 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it